quantdata-daily-bias

quantdata-daily-bias is a skill for Claude Code from celineycn/quantdata-plugin. It costs 167 tokens per session (9,179 once invoked), scanned A, original, MIT.

A market-analysis skill that reads current Brooks price-action events, a set of named patterns used in trading charts, from an HTTP API. It also reports measured bar shape and probabilities for how the US trading session may end.

In plain words
What is it for?
Use it to examine stocks, ETFs, futures, currency pairs, or crypto pairs. It reports range breakouts, follow-through, range position, long-range moves, climactic spikes, session-type probabilities, and bar-shape measurements.
Why use it?
It distinguishes measurements of prices already seen from predictions about what may happen next. Historical outcome rates and failure estimates provide context for current breakouts and other events.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the quantdata plugin — 3 skills shipped together

Good fit Use it to examine stocks, ETFs, futures, currency pairs, or crypto pairs. It reports range breakouts, follow-through, range position, long-range moves, climactic spikes, session-type probabilities, and bar-shape measurements.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/celineycn/quantdata-plugin/quantdata-daily-bias
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add celineycn/quantdata-plugin --skill quantdata-daily-bias
Clone the repo
git clone --depth 1 https://github.com/celineycn/quantdata-plugin

Made for: Claude Code.

Or install quantdata, the plugin that ships this one along with the rest of its 3 skills.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for quantdata-daily-bias

README.md
[![agentmods](https://agentmods.dev/badge/skills/celineycn/quantdata-plugin/quantdata-daily-bias/github.svg)](https://agentmods.dev/skills/celineycn/quantdata-plugin/quantdata-daily-bias)
Your own site
<a href="https://agentmods.dev/skills/celineycn/quantdata-plugin/quantdata-daily-bias"><img src="https://agentmods.dev/badge/skills/celineycn/quantdata-plugin/quantdata-daily-bias/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for quantdata-daily-bias

Your own site · 80×15
<a href="https://agentmods.dev/skills/celineycn/quantdata-plugin/quantdata-daily-bias"><img src="https://agentmods.dev/badge/skills/celineycn/quantdata-plugin/quantdata-daily-bias.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 167 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 9,179 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00167 $0.09179
Opus 5.5 $0.00067 $0.03672
Sonnet 5.5 $0.00033 $0.01836
Haiku 4.5 $0.00017 $0.00918

Measured 1mo ago against content hash b2dcd225c50c, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

quantdata-daily-bias scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

curl -s -H "X-API-Key: $QUANTDATA_API_KEY" \
quantdata/skills/quantdata-daily-bias/SKILL.md · 566 lines

How it starts

The opening of the file, as written. The whole thing — 566 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Quant Data — Brooks Events

An HTTP API that detects the classical Brooks price-action events in the window trading right now and attaches to each one the outcome rate measured for that exact event definition in that exact window — pre-registered, on sixteen years of S&P 500 futures data. Range breakouts additionally carry a calibrated per-event failure estimate.

Two further blocks travel with every read and answer different questions. day_type is a calibrated probability distribution over how the session in progress could resolve — a prediction, with published accuracy, available in the US day session only. shape is arithmetic over the bars that have already printed — a measurement, with no accuracy figure because nothing is being predicted, available in every window. Keeping those two apart is a hard rule of this skill; see "Two blocks that are not the same thing" below.

Base URL: https://api.quantdata.uk

Authentication

Send the header X-API-Key, with a key starting qd_. Read it from the environment variable QUANTDATA_API_KEY. Never write a key into this file, into code you generate, into a commit, or into a message back to the user.

export QUANTDATA_API_KEY="qd_..."

If the variable is unset, one anonymous first-look response may still succeed per source per UTC day. It is a complete response, and its legacy-named free_tier object has access_kind: "anonymous", calls_remaining_today, resets_at, and the next action.

For continued evaluation, ask the user which email address should receive a free key, then POST https://api.quantdata.uk/v1/access/free-key with JSON:

{"email":"[email protected]","marketing_opt_in":false,"source":"agent"}

An MCP-connected agent can call quantdata_request_free_api_key instead. No login, password, card or GUI is required. The raw qd_ key is delivered only to the inbox and never returned in the REST or MCP result. Never invent an email address.

marketing_opt_in defaults to false and is separate from key delivery. Set it to true only when the email owner explicitly asks for occasional product updates. A true request is only pending. It is confirmed only if the recipient replies SUBSCRIBE to the key-delivery email; no marketing updates are sent before confirmation. Do not report the request as a completed subscription. A free key covers all four Quant Data endpoints, sharing 10 successful calls per UTC day.

Read the full file on GitHub · 566 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 1mo ago First seen · 566 lines · 167 tokens per session scan A b2dcd225c50c

Subscribe to this mod's changes

quantdata-daily-bias is a skill published in the GitHub repository celineycn/quantdata-plugin (1 stars, last pushed 2mo ago), licensed MIT. It adds 167 tokens to every session and 9,179 once invoked, about $0.0007 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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